Abstract
Wetlands are critical ecosystems that deliver essential services such as water purification, flood regulation, and biodiversity support. Non-intertidal wetlands, in particular, play a key role in maintaining global ecological balance. However, due to their complex structures and dynamic nature, monitoring these ecosystems poses significant challenges. This study offers a comprehensive review of current remote sensing techniques applied to non-intertidal wetlands, with a focus on classification and mapping, vegetation and biodiversity assessment, hydrological monitoring, water quality evaluation, spatiotemporal dynamics, and ecosystem service quantification. We further examine the diverse data sources, analytical models, and technical tools used to monitor these ecosystems. Key challenges identified include limitations in spatial and temporal resolution, ecosystem complexity, and the difficulties of large-scale monitoring. To overcome these barriers, the paper explores promising future directions, including multi-source data integration, the advanced use of hyperspectral satellites, the application of artificial intelligence and machine learning, the coupling of ecological models with socio-economic data, and the development of a global non-intertidal wetland monitoring system. These strategies hold the potential to enhance scientific understanding, support effective conservation efforts, and facilitate sustainable management practices for wetland ecosystems.